At a Glance
- Tasks: Build and deploy AI systems for real drug discovery teams using cutting-edge technology.
- Company: Join an innovative AI-native drug discovery platform in central London.
- Benefits: Competitive salary, equity options, private medical insurance, and a pension scheme.
- Other info: Enjoy a collaborative culture with opportunities for remote work and career growth.
- Why this job: Make a real impact in drug discovery while working on exciting machine learning projects.
- Qualifications: Experience in machine learning, software engineering, and chemistry or molecular datasets required.
The predicted salary is between 60000 - 80000 € per year.
Build production AI systems used by real drug discovery teams. We are partnering with an emerging AI-native drug discovery company looking to hire a Machine Learning Engineer to help scale the predictive infrastructure behind its molecular design platform. The role is particularly suited to engineers who enjoy building production ML systems in scientific environments and want to work on real-world problems rather than isolated research projects. This role is full-time and on-site.
Our client is specifically looking for candidates who combine strong machine learning capability with hands-on software engineering experience and exposure to chemical or molecular datasets. This is not a purely academic research role. The focus is on building scalable infrastructure, deploying models, and improving prediction systems used in production.
Our client is an AI-native drug discovery platform focused on improving decision-making across medicinal chemistry and molecular design. The business has built a proprietary platform combining experimental molecular property data from patents, publications, partners, and internal sources to support predictive modelling in drug discovery that has gained adoption across global chemistry teams working in oncology, inflammation, dementia, and broader therapeutic areas. The company operates from central London with a collaborative, high-ownership culture combining expertise across machine learning, software engineering, chemistry, and biology.
- Build and deploy molecular property prediction models using real-world chemical datasets.
- Develop and improve ML infrastructure including training pipelines, experiment tracking, model registries, and CI/CD workflows.
- Support production deployment of machine learning systems and scalable cloud infrastructure.
- Improve model validation strategies, monitoring, and performance evaluation.
- Contribute to scalable scientific software and platform architecture.
- Prepare technical documentation and support scientific presentations where required.
Industry experience building and deploying machine learning systems in production environments. Strong software engineering fundamentals and experience shipping production code. Experience applying machine learning within chemistry, molecular property prediction, cheminformatics, or related scientific domains. Strong understanding of ML fundamentals including validation strategy, overfitting, and model performance evaluation. Ability to work collaboratively across engineering and scientific teams. AWS, GCP, or Azure infrastructure experience. Infrastructure-as-code and scalable deployment workflows. Open-source scientific software contributions. PhD or advanced academic background in chemistry, computational chemistry, computer science, or related disciplines.
Competitive salary and equity options package. Opportunity to shape core ML infrastructure within a growing AI drug discovery platform. Private medical insurance. Pension scheme. One week remote working per quarter. Cycle to Work scheme.
Machine Learning Engineer - Hybrid Remote in London employer: Aspire Life Sciences Search
Join a pioneering AI-native drug discovery platform in the heart of London, where you will have the opportunity to build impactful machine learning systems that directly contribute to real-world medicinal chemistry challenges. With a collaborative culture that values ownership and expertise across diverse scientific fields, you will benefit from competitive salaries, equity options, private medical insurance, and a pension scheme, alongside unique opportunities for professional growth and development in a cutting-edge environment. Experience the thrill of working on meaningful projects while enjoying the flexibility of hybrid remote work and a supportive workplace that encourages innovation.
Contact Detail:
Aspire Life Sciences Search Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Hybrid Remote in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to chemistry or molecular datasets. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your experience with ML systems and how you've tackled real-world problems. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Machine Learning Engineer - Hybrid Remote in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your machine learning and software engineering experience, especially in scientific environments. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about building production ML systems in drug discovery. Let us know how your background in chemistry or molecular datasets makes you a perfect fit for our team.
Showcase Your Projects:If you've worked on any relevant projects, whether in a professional setting or as personal endeavours, make sure to mention them. We love seeing practical applications of your skills, especially if they relate to molecular property prediction or similar areas.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it shows us you’re keen to join our collaborative culture!
How to prepare for a job interview at Aspire Life Sciences Search
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially around validation strategies and model performance evaluation. Be ready to discuss how you've applied these concepts in real-world scenarios, particularly in the context of chemical or molecular datasets.
✨Showcase Your Software Engineering Skills
Prepare to talk about your hands-on software engineering experience. Highlight specific projects where you’ve built and deployed production ML systems, focusing on your coding practices and any CI/CD workflows you've implemented.
✨Familiarise Yourself with the Company’s Focus
Research the company’s AI-native drug discovery platform and understand their approach to predictive modelling. Be prepared to discuss how your skills can contribute to improving decision-making in medicinal chemistry and molecular design.
✨Collaborative Mindset is Key
Emphasise your ability to work collaboratively across engineering and scientific teams. Share examples of how you've successfully collaborated in past roles, as this position values a high-ownership culture and teamwork.
